AIMC Topic: Visual Cortex
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The feature-weighted receptive field: an interpretable encoding model for complex feature spaces.
NeuroImage
Jun 20, 2017
We introduce the feature-weighted receptive field (fwRF), an encoding model designed to balance expressiveness, interpretability and scalability. The fwRF is organized around the notion of a feature map-a transformation of visual stimuli into visual ...
Edge detection based on Hodgkin-Huxley neuron model simulation.
Cognitive processing
Apr 3, 2017
In this paper, we propose a spiking neural network model for edge detection in images. The proposed model is biologically inspired by the mechanisms employed by natural vision systems, more specifically by the biologically fulfilled function of simpl...
Extending the Stabilized Supralinear Network model for binocular image processing.
Neural networks : the official journal of the International Neural Network Society
Mar 18, 2017
The visual cortex is both extensive and intricate. Computational models are needed to clarify the relationships between its local mechanisms and high-level functions. The Stabilized Supralinear Network (SSN) model was recently shown to account for ma...
Unsupervised frequency-recognition method of SSVEPs using a filter bank implementation of binary subband CCA.
Journal of neural engineering
Jan 10, 2017
OBJECTIVE: Recently developed effective methods for detection commands of steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) that need calibration for visual stimuli, which cause more time and fatigue prior to the use, ...
Humans
Female
Reproducibility of Results
Adult
Electroencephalography
Signal Processing, Computer-Assisted
Pattern Recognition, Automated
Brain-Computer Interfaces
Sensitivity and Specificity
Male
Unsupervised Machine Learning
Data Interpretation, Statistical
Evoked Potentials, Visual
Visual Perception
Statistics as Topic
Brain Waves
Visual Cortex
Automated selection of brain regions for real-time fMRI brain-computer interfaces.
Journal of neural engineering
Nov 30, 2016
OBJECTIVE: Brain-computer interfaces (BCIs) implemented with real-time functional magnetic resonance imaging (rt-fMRI) use fMRI time-courses from predefined regions of interest (ROIs). To reach best performances, localizer experiments and on-site exp...
Visual Perception
Visual Cortex
Word Processing
Magnetic Resonance Imaging
Unsupervised Machine Learning
Brain Mapping
Principal Component Analysis
Brain-Computer Interfaces
Task Performance and Analysis
Nerve Net
Adult
Sensitivity and Specificity
Male
Humans
Computer Systems
Female
Reproducibility of Results
Neural network model develops border ownership representation through visually guided learning.
Neurobiology of learning and memory
Oct 13, 2016
As Rubin's famous vase demonstrates, our visual perception tends to assign luminance contrast borders to one or other of the adjacent image regions. Experimental evidence for the neuronal coding of such border-ownership in the primate visual system h...
Comparison of deep neural networks to spatio-temporal cortical dynamics of human visual object recognition reveals hierarchical correspondence.
Scientific reports
Jun 10, 2016
The complex multi-stage architecture of cortical visual pathways provides the neural basis for efficient visual object recognition in humans. However, the stage-wise computations therein remain poorly understood. Here, we compared temporal (magnetoen...
Models of visual categorization.
Wiley interdisciplinary reviews. Cognitive science
Mar 20, 2016
Visual categorization refers to our ability to organize objects and visual scenes into discrete categories. It is an essential skill as it allows us to distinguish friend from foe or edible versus poisonous food. Understanding how the visual system c...
Atoms of recognition in human and computer vision.
Proceedings of the National Academy of Sciences of the United States of America
Feb 16, 2016
Discovering the visual features and representations used by the brain to recognize objects is a central problem in the study of vision. Recently, neural network models of visual object recognition, including biological and deep network models, have s...
Multivoxel Object Representations in Adult Human Visual Cortex Are Flexible: An Associative Learning Study.
Journal of cognitive neuroscience
Feb 2, 2016
Learning associations between co-occurring events enables us to extract structure from our environment. Medial-temporal lobe structures are critical for associative learning. However, the role of the ventral visual pathway (VVP) in associative learni...
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